Artificial potential field obstacle avoidance method for omnidirectional-wheel mobile robot

Abstract

The invention discloses an artificial potential field obstacle avoidance method for an omnidirectional-wheel mobile robot. The method comprises: S1, acquiring an initial position and a final target position of a mobile robot; S2, carrying out clustering on laser radar environment data and completing local environment modeling based on a least squares method; S3, acquiring a current time position of the mobile robot and a local target point within a laser radar scanning range; S4, establishing a fuzzy rule library by combining fuzzy controlling, selecting a marching mode, and quantifying the speed of the mobile robot based on a force size and a deflection degree; S5, controlling the robot to walk; and S6, detecting whether the mobile robot reaches the final target point; if not, returning to the S2 and carrying out cyclic execution; and if so, ending the marching process. Therefore, the omnidirectional-wheel mobile robot is able to select an own marking mode adaptively and takes different passing paths according to different obstacles; the advantage of the omnidirectional wheel is utilized fully; and the obstacle passing ability of the robot is enhanced.

Description

technical field [0001] The invention relates to the technical field of traffic information, in particular to an artificial potential field obstacle avoidance method suitable for omnidirectional wheel mobile robots. Background technique [0002] Today, with the vigorous development of intelligent automation, mobile robots are leading this technological revolution. Mobile robots can not only undertake handling tasks and improve work efficiency, but also have unique advantages in monitoring and emergency response. With the continuous innovation of mobile robot technology, it has a wide range of applications in agriculture, industry, and national defense. [0003] Path planning technology is one of the key technologies of mobile robots. According to known or unknown environmental information, it can be divided into offline path planning and online path planning. The former path is better, while the latter has strong real-time performance and strong adaptability. The invention...

AI Technical Summary

Problems solved by technology

Compared with ordinary wheeled mobile robots, the moving process of omnidirectional mobile robots is more complicated, and point-to-point movement has multiple moving modes. Due to the advantages of the steering wheel, there is an urgent need for an obstacle avoidance method with high efficiency, high real-time performance, and strong passing ability, which is suitable for all-round mobile robots.

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